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Interpreting Changes in SPX–VIX Correlation

Article Quant Q&A · Author: jessica

Summary

The document discusses why the usual inverse relationship between the S&P 500 and VIX can weaken or turn positive. Its answer suggests that the asymmetry of option demand matters: during market declines, investors may buy options for protection, while rising markets do not necessarily force implied volatility lower. It also proposes checking option skew and comparing recent realized volatility with implied volatility when studying these episodes.

The discussion offers plausible mechanisms and exploratory variables, rather than a tested forecast of future returns. It does not establish that a correlation shift predicts a particular market direction, and the claim that the inverse relationship is stronger during declines is presented as explanation, not demonstrated with data. Tick-level analysis is suggested, but no such analysis or empirical results are included.

Key ideas

  • SPX and VIX often move inversely, but their relationship can weaken or become positive.
  • Option demand for downside protection may help explain stronger negative co-movement during market declines.
  • Option skew and the gap between recent realized volatility and implied volatility may help contextualize correlation changes.
  • The document does not show that correlation breakdowns reliably predict future returns.

Tags

Full text
# When the Inverse Correlation between the SPX and VIX breaks down


# When the Inverse Correlation between the SPX and VIX breaks down












As we all know the S&P and its implied vol, the VIX, generally move in opposite direction. To a large extent, the correlations makes sense. IV is one of the main drivers of the price of options, going long options is also going long IV. When the market drops, option prices, adjusted for the drop in the the S&P price, experience a further appreciation, the extra appreciation o the options above and beyond the the price movement can be attributed to an increase in IV. My question is when IV(the VIX) and SPX correlation breakdown from its usual inverse relationship( corr=-.95), what do you think this implies about future returns? Why does these instances occur? There are many times when the correlations drops to 0 and becomes positive!

Below is a picture with the 20 day correlation between the two indices.

## Answer by Andrew (score 7, accepted)

https://quant.stackexchange.com/a/8022

If you look at tick data, you will probably get an even better analysis. However, vix correlation tends to be negative with spx but remember that this is generally more true for when spx tanks. When spx goes up, the correlation isn't as strong. Why? People panic after a drop, therefore leading to people buying options. They don't care about black scholes delta hedging etc. They only want to hedge their position. However, when spot is going up, vix doesn't necessarily have to go down because if it does go down quite a bit, you buy the option, and just delta hedge and collect the difference between realized and implied volatility.

Another thing that you can also look at is the skew in the options market. When correlation between spot and vol is very high, you tend find a much steeper skew and vice versa.

spx is cash settled so there is no physical to deliver. and spx is so liquid that it is nearly impossible for any individual to move the market. we know that market impact is proportional to sigma * sqrt( (order size) / (average volume) ). on any given day, spx and spy trades at least 2 million contracts. for a big player to move the market, you will literally need to trade at least half a billion which I've personally never seen.

You should do an analysis of realized volatility during the previous 20 days as well. If the realized volatility during the previous 20 days was .16, and the implied volatility was .12, you will still buy the option even if markets were going up no? since you can make a profit from delta hedging.

Shown in full with attribution under the source's licence. Licence: CC BY-SA 4.0 (Stack Exchange)

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.